← Authors

Joern-Henrik Jacobsen

15 papers · 2019–2025 · 5 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (5) 🐝 Cross-Pollinator (11) πŸ—ΊοΈ Taxonomy Completionist (20) πŸƒ Academic Marathon (6) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge πŸ‘‘ Triple Crown πŸ—ƒοΈ Keyword Collector (56) ⚑ Prolific Year (5) πŸš€ Conference Pioneer πŸ’Ž Century Club (15)

Conferences

ICML (8) ICLR (3) NIPS (2) AISTATS (1) CLEAR (1)

Top co-authors

Jens Behrmann (6) Richard Zemel (5) Will Grathwohl (4) Kuan-Chieh Wang (3) David Duvenaud (3) Elliot Creager (2) Kevin Swersky (2) Ricky T. Q. Chen (2) Nicholas Carlini (1) David K. Duvenaud (1)

Keywords

domain generalization (3) density estimation (2) adversarial robustness (2) maximum likelihood (2) normalizing flow (2) invertible residual network (2) generative model (2) covariate shift (1) algorithmic fairness (1) representation learning (1) adversarial training (1) out-of-distribution generalization (1) optimal transport (1) convolutional network (1) model robustness (1) disentangled representation (1) gradient computation (1) distribution shift (1) domain adaptation (1) robust optimization (1)

Papers

Addressing Misspecification in Simulation-based Inference through Data-driven Calibration ICML 2025
Learning Invariant Representations with Missing Data CLEAR 2022
Environment Inference for Invariant Learning ICML 2021
Out-of-Distribution Generalization via Risk Extrapolation (REx) ICML 2021
Understanding and Mitigating Exploding Inverses in Invertible Neural Networks AISTATS 2021
How to Train Your Neural ODE: the World of Jacobian and Kinetic Regularization ICML 2020
Fundamental Tradeoffs between Invariance and Sensitivity to Adversarial Perturbations ICML 2020
Understanding the Limitations of Conditional Generative Models ICLR 2020
Your classifier is secretly an energy based model and you should treat it like one ICLR 2020
Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling ICML 2020
Invertible Residual Networks ICML 2019
Residual Flows for Invertible Generative Modeling NIPS 2019
Excessive Invariance Causes Adversarial Vulnerability ICLR 2019
Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks NIPS 2019
Flexibly Fair Representation Learning by Disentanglement ICML 2019